Impacts of the Type I Toxin-Antitoxin System, SprG1/SprF1, on Staphylococcus aureus Gene Expression.

Type I toxin-antitoxin (TA) systems are widespread genetic modules in bacterial genomes. They express toxic peptides whose overexpression leads to growth arrest or cell death, whereas antitoxins regulate the expression of toxins, acting as labile antisense RNAs. The Staphylococcus aureus (S. aureus) genome contains and expresses several functional type I TA systems, but their biological functions remain unclear. Here, we addressed and challenged experimentally, by proteomics, if the type I TA system, the SprG1/SprF1 pair, influences the overall gene expression in S. aureus. Deleted and complemented S. aureus strains were analyzed for their proteomes, both intracellular and extracellular, during growth. Comparison of intracellular proteomes among the strains points to the SprF1 antitoxin as moderately downregulating protein expression. In the strain naturally expressing the SprG1 toxin, cytoplasmic proteins are excreted into the medium, but this is not due to unspecific cell leakages. Such a toxin-driven release of the cytoplasmic proteins may modulate the host inflammatory response that, in turn, could amplify the S. aureus infection spread.

Human skin microbiota-friendly lysostaphin.

Growing antibiotic resistance of bacteria is a burning problem of human and veterinary medicine. Expansion and introduction of novel microbicidal therapeutics is highly desirable. However, antibiotic treatment disturbs the balance of physiological microbiota by changing its qualitative and/or quantitative composition, resulting in a number of adverse effects that include secondary infections. Although such dysbiosis may be reversed by the treatment with probiotics, a more attractive alternative is the use of antibiotics that target only pathogens, while sparing the commensals. Here, we describe lysostaphin LSp222, an enzyme produced naturally by Staphylococcus pseudintermedius 222. LSp222 is highly effective against S. aureus, including its multi-drug resistant strains. Importantly, the inhibitory concentration for S. epidermidis, the predominant commensal in healthy human skin, is at least two orders of magnitude higher compared to S. aureus. Such significant therapeutic window makes LSp222 a microbiota-friendly antibacterial agent with a potential application in the treatment of S. aureus-driven skin infections.

Application of Two-Dimensional Difference Gel Electrophoresis in Identification of Factors Responsible for Virulence of Staphylococcus aureus.

Staphylococcus aureus is a dangerous opportunistic pathogen of humans and animals. Highly virulent and multi-antibiotic-resistant strains are of particular concern due to high invasiveness and limited array of useful treatment options. Proteomics allows identification and investigation of staphylococcal virulence factors to better understand and treat the related disease. Two-dimensional difference gel electrophoresis (2D DIGE) is a powerful method for identification of differences in staphylococcal proteomes, both intracellular and secretory. Not only the presence of particular proteins and their quantities may be determined, but also each modification changing the molecular mass and/or isoelectric point of a protein is trackable. Especially, 2D DIGE allows for detection of posttranslational modifications, including processing and degradation by proteases. For differential analysis, protein samples are labeled with spectrally distinguishable fluorescent dyes, mixed and separated according to their isoelectric point (first dimension), and then electrophoresed in the presence of sodium dodecyl sulfate according to their molecular mass (second dimension). Exceptional resolution of 2D DIGE allows to obtain focused and sharp protein spots, and identify a large number of differentiating proteins. Here we provide protocols for TRI Reagent-based preparation of high-quality samples for 2D DIGE, sample separation, and ways of handling differentiating protein spots which lead to samples ready for protein identification using MS.